The Extractive Industries Transparency Initiative (EITI): exploring global extractive firms’ interpretation of EITI initiatives in Ghana’s mining sector amidst institutional complexity
Bibliographic record
Abstract
The Extractive Industries Transparency Initiative (EITI) is a global governance initiative that has the primary goal of promoting greater transparency and accountability concerning the use of royalties paid by global extractive firms to governments. Global extractive firms are largely supportive of EITI and most African countries are members of the initiative. However, research findings presented in this study concerning the Ghana EITI (GHEITI) suggest that global extractive firms are not seeing stronger visibility or impact of their payments to government reflected in mining areas. A thematic analysis of interviews conducted with mining managers from four global mining firms operating in Ghana demonstrates that managerial perspectives centre on how GHEITI relates to securing and maintaining the legitimacy of the business of mining. Through the adoption of an institutionalist approach, the paper demonstrates the broader theoretical and empirical implications for global extractive firms operating in complex institutional settings in African countries where EITI is implemented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".